Market Collective Wisdom Discovery for Portfolio Investments

Q3 Engineering
P. Juszczuk, I. Kaliszewski, D. Podkopaev, H. Shih
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引用次数: 3

Abstract

The goal of numerous investing strategies, as opposed to hedging strategies, is "to beat the market", i.e. to secure returns higher than those guaranteed by tracking market indices. In order to achieve this goal, one needs to identify key factors which drive markets and cause security prices to fluctuate. We assume that distinctive key market factors exist, though it is not known how such factors correlate and aggregate, and eventually push a market from one quotation to another. In other words, we purport that at a given time there is the collective wisdom in a market which shapes the collective investment pattern for the future. We engage ourselves to reverse engineer that wisdom. Specifically, we attempt to reverse engineer it from market returns (which we interpret as collective market wisdom embodiment) with the use of the notions of vectors of concessions and compromise half lines, recently introduced into Multiple Criteria Decision Analysis. We illustrate our approach with preliminary calculations for selecting portfolios of international investment funds.
证券投资的市场集体智慧发现
与对冲策略相反,许多投资策略的目标是“战胜市场”,即确保比跟踪市场指数所保证的回报更高的回报。为了实现这一目标,需要确定驱动市场和导致证券价格波动的关键因素。我们假设存在独特的关键市场因素,尽管不知道这些因素如何相互关联和汇总,并最终推动市场从一个报价到另一个报价。换句话说,我们认为,在给定的时间,市场中存在集体智慧,这种智慧塑造了未来的集体投资模式。我们致力于逆向工程这种智慧。具体来说,我们试图利用最近引入多标准决策分析的让步向量和妥协半线的概念,从市场回报(我们将其解释为集体市场智慧的体现)中对其进行逆向工程。我们用选择国际投资基金投资组合的初步计算来说明我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Information and Management Sciences
International Journal of Information and Management Sciences Engineering-Industrial and Manufacturing Engineering
CiteScore
0.90
自引率
0.00%
发文量
0
期刊介绍: - Information Management - Management Sciences - Operation Research - Decision Theory - System Theory - Statistics - Business Administration - Finance - Numerical computations - Statistical simulations - Decision support system - Expert system - Knowledge-based systems - Artificial intelligence
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